BSc Mathematics with Data Science
Entry requirements
A level: AAA or AABB including Mathematics (grade A) IB: Pass, with 36 points overall with 18 at Higher Level, including 6 points from Higher Level Mathematics (Preferred Mathematics module is Analysis and Approaches, but Applications and Interpretation also considered)
About this course
Bachelor of Science in Mathematics with Data Science, a mathematics degree centred on mathematical theory and computation. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Project Management, Environmental Analysis, and Artificial Intelligence & Machine Learning. Students complete a compulsory final-year project alongside core training. The first year covers foundational topics through Calculus I, Calculus II, Computational Mathematics, and Introduction to Statistics. The second year progresses into specialised computational and statistical concepts through Fundamentals of Data Science in R, Numerical Analysis, Partial Differential Equations, and Statistical Inference. In the final year, students tackle advanced topics such as Machine Learning and the Mathematics Project, while tailoring their studies through optional modules spanning diverse branches of applied and pure mathematics.
Modules
- Calculus I
- Calculus II
- Computational Mathematics
- Core Skills for Mathematicians I
- Dynamics and Relativity
- First Year Mathematics Workshop
- Introduction to Statistics
- Linear Algebra I
- Linear Algebra II
- Number Theory
- Analysis
- Core Skills for Mathematicians II
- Fundamentals of Data Science in R
- Numerical Analysis
- Partial Differential Equations
- Statistical Inference
- Statistical Modelling I
- Algorithms
- Fields and Fluids
- Financial Mathematics
- Geometry and Topology
- Graph Theory
- Group Theory
- Introduction to Operational Research
- Stochastic Processes
- Vector Calculus and Complex Variable Theory
- Machine Learning
- Mathematics Project
- Actuarial Mathematics I
- Actuarial Mathematics II
- Advanced Fluid Dynamics
- Advanced Partial Differential Equations
- Algebraic Topology
- Complex Analysis
- Complex and Integral Transform Methods
- Computational Statistical Inference
- Design and Analysis of Experiments
- Further Number Theory and Cryptography
- Galois Theory
- Geometry and Data
- Global Health
- Global Sustainability Challenges
- Hilbert Spaces
- Infinite Groups
- Learning and Teaching Mathematics
- Mathematical Biology
- Mathematical Finance
- Mathematical Programming
- Numerical Partial Differential Equations
- Optimization
- Project Management
- Relativity, Black Holes and Cosmology
- Statistical Methods in Insurance
- Statistical Modelling II
- Structure and Dynamics of Networks
- Survival Models